send formatted msg to glog

[liufengwei0103]

效果图：

[daquexian]

这里的调用方式不需要这么迂回，直接返回 maybe_error.Data_YouAreNotAllowedToCallThisFuncOutsideThisFile() 就可以了

[liufengwei0103]

这里的调用方式不需要这么迂回，直接返回 maybe_error.Data_YouAreNotAllowedToCallThisFuncOutsideThisFile() 就可以了

不是吧，这里调用Data_YouAreNotAllowedToCallThisFuncOutsideThisFile这个函数只会返回T data。 这里本来的意思是，如果FormatErrorStr失败了，返回错误栈原来的呈现方式，FormatErrorStr的错误栈就不需要了。

[daquexian]

哦哦，了解了。添加一个注释吧

[liufengwei0103]

哦哦，了解了。添加一个注释吧

已加

[daquexian]

这一行是不是没必要

[liufengwei0103]

这一行是不是没必要

后面会调用这个函数，这里提前声明一下。否则需要include一下声明这个函数的文件（目前没有声明，只有定义）。

[liufengwei0103]

这一行是不是没必要

太多文件编译依赖maybe.h，如果include的方式，被include的文件的改动，会造成大量重新编译。

[github-actions]

Speed stats:

GPU Name: GeForce GTX 1080 

OneFlow resnet50 time: 127.5ms (= 6372.5ms / 50, input_shape=[16, 3, 224, 224], backward is enabled)
OneFlow GPU used (rank 0): 0 MiB
PyTorch resnet50 time: 139.7ms (= 6983.3ms / 50, input_shape=[16, 3, 224, 224], backward is enabled)
PyTorch GPU used (rank 0, estimated): 0 MiB
Relative speed: 1.10 (= 139.7ms / 127.5ms)

OneFlow resnet50 time: 74.1ms (= 3707.0ms / 50, input_shape=[8, 3, 224, 224], backward is enabled)
OneFlow GPU used (rank 0): 0 MiB
PyTorch resnet50 time: 85.2ms (= 4257.9ms / 50, input_shape=[8, 3, 224, 224], backward is enabled)
PyTorch GPU used (rank 0, estimated): 0 MiB
Relative speed: 1.15 (= 85.2ms / 74.1ms)

OneFlow resnet50 time: 50.0ms (= 2499.2ms / 50, input_shape=[4, 3, 224, 224], backward is enabled)
OneFlow GPU used (rank 0): 0 MiB
PyTorch resnet50 time: 57.5ms (= 2873.3ms / 50, input_shape=[4, 3, 224, 224], backward is enabled)
PyTorch GPU used (rank 0, estimated): 0 MiB
Relative speed: 1.15 (= 57.5ms / 50.0ms)

OneFlow resnet50 time: 42.3ms (= 2114.1ms / 50, input_shape=[2, 3, 224, 224], backward is enabled)
OneFlow GPU used (rank 0): 0 MiB
PyTorch resnet50 time: 48.4ms (= 2418.3ms / 50, input_shape=[2, 3, 224, 224], backward is enabled)
PyTorch GPU used (rank 0, estimated): 0 MiB
Relative speed: 1.14 (= 48.4ms / 42.3ms)

OneFlow resnet50 time: 39.8ms (= 1988.3ms / 50, input_shape=[1, 3, 224, 224], backward is enabled)
OneFlow GPU used (rank 0): 0 MiB
PyTorch resnet50 time: 43.4ms (= 2171.1ms / 50, input_shape=[1, 3, 224, 224], backward is enabled)
PyTorch GPU used (rank 0, estimated): 0 MiB
Relative speed: 1.09 (= 43.4ms / 39.8ms)

OneFlow resnet50 time: 148.1ms (= 7402.8ms / 50, input_shape=[16, 3, 224, 224], backward is enabled)
OneFlow GPU used (rank 0): 0 MiB
PyTorch resnet50 time: 152.3ms (= 7615.9ms / 50, input_shape=[16, 3, 224, 224], backward is enabled)
PyTorch GPU used (rank 0, estimated): 0 MiB
Relative speed: 1.03 (= 152.3ms / 148.1ms)

OneFlow resnet50 time: 91.9ms (= 4595.3ms / 50, input_shape=[8, 3, 224, 224], backward is enabled)
OneFlow GPU used (rank 0): 0 MiB
PyTorch resnet50 time: 96.4ms (= 4818.0ms / 50, input_shape=[8, 3, 224, 224], backward is enabled)
PyTorch GPU used (rank 0, estimated): 0 MiB
Relative speed: 1.05 (= 96.4ms / 91.9ms)

OneFlow resnet50 time: 63.7ms (= 3187.2ms / 50, input_shape=[4, 3, 224, 224], backward is enabled)
OneFlow GPU used (rank 0): 0 MiB
PyTorch resnet50 time: 68.9ms (= 3443.6ms / 50, input_shape=[4, 3, 224, 224], backward is enabled)
PyTorch GPU used (rank 0, estimated): 0 MiB
Relative speed: 1.08 (= 68.9ms / 63.7ms)

OneFlow resnet50 time: 57.6ms (= 2878.8ms / 50, input_shape=[2, 3, 224, 224], backward is enabled)
OneFlow GPU used (rank 0): 0 MiB
PyTorch resnet50 time: 56.4ms (= 2818.9ms / 50, input_shape=[2, 3, 224, 224], backward is enabled)
PyTorch GPU used (rank 0, estimated): 0 MiB
Relative speed: 0.98 (= 56.4ms / 57.6ms)

OneFlow resnet50 time: 61.1ms (= 3056.9ms / 50, input_shape=[1, 3, 224, 224], backward is enabled)
OneFlow GPU used (rank 0): 0 MiB
PyTorch resnet50 time: 48.3ms (= 2414.1ms / 50, input_shape=[1, 3, 224, 224], backward is enabled)
PyTorch GPU used (rank 0, estimated): 0 MiB
Relative speed: 0.79 (= 48.3ms / 61.1ms)